Completing the Forecast: Characterizing and Communicating Uncertainty for Better Decisions Using Weather and Climate Forecasts (2006)

Each report is produced by a committee of experts selected
by the Academy to address a particular statement of task and
is subject to a rigorous, independent peer review; while the
reports represent views of the committee, they also are
endorsed by the Academy.
Learn more on our expert consensus reports.

Uncertainty is a fundamental characteristic of weather, seasonal climate, and hydrological prediction, and no forecast is complete without a description of its uncertainty. Effective communication of uncertainty helps people better understand the likelihood of a particular event and improves their ability to make decisions based on the forecast. Nonetheless, for decades, users of these forecasts have been conditioned to receive incomplete information about uncertainty. They have become used to single-valued (deterministic) forecasts (e.g., &quot;the high temperature will be 70 degrees Farenheit 9 days from now&quot;) and applied their own experience in determining how much confidence to place in the forecast. Most forecast products from the public and private sectors, including those from the National Oceanographic and Atmospheric Administration\u0092s National Weather Service, continue this deterministic legacy. Fortunately, the National Weather Service and others in the prediction community have recognized the need to view uncertainty as a fundamental part of forecasts. By partnering with other segments of the community to understand user needs, generate relevant and rich informational products, and utilize effective communication vehicles, the National Weather Service can take a leading role in the transition to widespread, effective incorporation of uncertainty information into predictions. &quot;Completing the Forecast&quot; makes recommendations to the National Weather Service and the broader prediction community on how to make this transition.

Key Messages

Enhanced Enterprise-wide educational initiatives will underpin efforts to improve communication and use of uncertainty information. There are three critical areas of focus: (1) undergraduate and graduate education, (2) recurrent forecaster training, and (3) user outreach and education.

Hydrometeorological services in the United States are an Enterprise effort. Therefore, effective incorporation of uncertainty information will require a fundamental and coordinated shift by all sectors of the Enterprise.

Incorporating uncertainty in forecasts will require not only the attention but also the advocacy of NWS management.

Only through comprehensive interaction with the Enterprise will NWS be able to move toward effective and widespread estimation and communication of uncertainty information. One mechanism for engaging the entire Enterprise on this and related topics is an independent NWS advisory committee with broad representation.

Testbeds are emerging as a useful mechanism for developing and testing new approaches and methodologies in estimating, communicating, and using uncertainty information. The effectiveness of testbeds is limited when all appropriate sectors of the Enterprise are not included.

The ability of NOAA to distribute and communicate uncertainty information is predicated on the capacity to produce post-processed probabilistic model guidance on a variety of spatial scales. Currently, NOAA maintains long-range (global) and short-range ensemble13 prediction systems.

To make effective use of uncertainty products, users need complete forecast verification information that measures all relevant aspects of forecast performance.

Understanding user needs and effectively communicating the value of uncertainty information for addressing those needs are perhaps the largest and most important tasks for the Enterprise. Yet, forecast information is often provided without full understanding of user needs or how to develop products that best support user decisions.

Statistics) already produce a wide variety of uncertainty information. However, both the model output and statistical information regarding its skill15 are difficult to access from outside NCEP. Thus, NWS is missing an opportunity to provide the underlying datasets that can drive improved uncertainty estimation and communication across the Enterprise.